Testing the accuracy of luminance maps acquired by smart phone cameras

This paper looks at the accuracy of using the built-in camera of smart phones and free software as an economical way to quantify and analyse light exposure by producing luminance maps from High Dynamic Range (HDR) images. HDR images were captured with an Apple iPhone 4S to capture a wide variation of luminance within an indoor and outdoor scene. The HDR images were then processed using Photosphere software (Ward, 2010.) to produce luminance maps, where individual pixel values were compared with calibrated luminance meter readings. This comparison has shown an average luminance error of ~8% between the HDR image pixel values and luminance meter readings, when the range of luminances in the image is limited to approximately 1,500cd/m2.

Green office interiors in Australia : lessons learnt

In 2003, the Green Building Council of Australia (GBCA) launched their Green Star rating tools for various types of buildings in order to promote green building practice in Australia. Of these, the Green Star-Office Interior rating tool is designed for building owners, tenants and interior designers to assess the environmental impact of an interior fitout. It covers a number of categories, including Management, Indoor Environment Quality, Energy, Transport, Water, Materials, Land Use and Ecology, Emissions, and Innovation. This paper reviews the usage of the Green Star system in Australian office tenancy fitouts and the potential challenges associated with Green Star-Office Interior implementation. This involves the analysis of score sheets of 66 office interior projects across Australia that achieved Green Star certification. The percentage of green star points obtained within each category and sub-categories (credits) for each project are investigated to illustrate the achievement of credits. The results show that Emission-related credits and Innovation related credits are the easiest and most difficult respectively to obtain. It is also found that 6 Green Star office interior projects perform especially better in the categories of Energy and Ecology than 4 and 5 Star projects. The investigation of point frequency in each category provides prospective Green Star applicants with insights into credit achievement for future projects.

Learning in host selection in Helicoverpa armigera (Hubner) (Lepidoptera : Noctuidae)

The effect of experience on pre- and post-alighting host selection in adult female Helicoverpa armigera was tested in an indoor flight cage, and in a large greenhouse. The moths had experienced either tobacco or tomato plants (both are hosts of H. armigera) for 3 days, or were given no experience. Individuals were then released and their host selection assessed. All individuals caught in the greenhouse were identified and tested for post-alighting acceptance on each host. Experience significantly influenced both pre- and post-alighting host selection in ovipositing moths. This modification in behaviour is attributed to 'learning', and presents the first detailed evidence for learning in moths. Possible behavioural mechanisms involved are discussed, and a hypothesis is presented regarding learning in post-alighting host acceptance. The existence of learning in H. armigera, a highly polyphagous agricultural pest, is discussed in the light of current theories on environmental predictability and the advantages of learning. Copyright 1998 The Association for the Study of Animal Behaviour.

Children exposure assessment to ultrafine particles and black carbon: The role of transport and cooking activities

An accurate evaluation of the airborne particle dose-response relationship requires detailed measurements of the actual particle concentration levels that people are exposed to, in every microenvironment in which they reside. The aim of this work was to perform an exposure assessment of children in relation to two different aerosol species: ultrafine particles (UFPs) and black carbon (BC). To this purpose, personal exposure measurements, in terms of UFP and BC concentrations, were performed on 103 children aged 8-11 years (10.1 ± 1.1 years) using hand-held particle counters and aethalometers. Simultaneously, a time-activity diary and a portable GPS were used to determine the children’s daily time-activity pattern and estimate their inhaled dose of UFPs and BC. The median concentration to which the study population was exposed was found to be comparable to the high levels typically detected in urban traffic microenvironments, in terms of both particle number (2.2×104 part. cm-3) and BC (3.8 μg m-3) concentrations. Daily inhaled doses were also found to be relatively high and were equal to 3.35×1011 part. day-1 and 3.92×101 μg day-1 for UFPs and BC, respectively. Cooking and using transportation were recognized as the main activities contributing to overall daily exposure, when normalized according to their corresponding time contribution for UFPs and BC, respectively. Therefore, UFPs and BC could represent tracers of children exposure to particulate pollution from indoor cooking activities and transportation microenvironments, respectively.

Energy-pollution nexus for urban buildings

Since the first oil crisis in 1974, economic reasons placed energy saving among the top priorities in most industrialised countries. In the decades that followed, another, equally strong driver for energy saving emerged: climate change caused by anthropogenic emissions, a large fraction of which result from energy generation. Intrinsically linked to energy consumption and its related emissions is another problem: indoor air quality. City dwellers in industrialised nations spend over 90% of their time indoors and exposure to indoor pollutants contributes to ~2.6% of global burden of disease and nearly 2 million premature deaths per year1. Changing climate conditions, together with human expectations of comfortable thermal conditions, elevates building energy requirements for heating, cooling, lighting and the use of other electrical equipment. We believe that these changes elicit a need to understand the nexus between energy consumption and its consequent impact on indoor air quality in urban buildings. In our opinion the key questions are how energy consumption is distributed between different building services, and how the resulting pollution affects indoor air quality. The energy-pollution nexus has clearly been identified in qualitative terms; however the quantification of such a nexus to derive emissions or concentrations per unit energy consumption is still weak, inconclusive and requires forward thinking. Of course, various aspects of energy consumption and indoor air quality have been studied in detail separately, but in-depth, integrated studies of the energy-pollution nexus are hard to come by. We argue that such studies could be instrumental in providing sustainable solutions to maintain the trade-off between the energy efficiency of buildings and acceptable levels of air pollution for healthy living.

GrabCutSFM : how 3D information improves unsupervised object segmentation

In this paper, we present an unsupervised graph cut based object segmentation method using 3D information provided by Structure from Motion (SFM), called Grab- CutSFM. Rather than focusing on the segmentation problem using a trained model or human intervention, our approach aims to achieve meaningful segmentation autonomously with direct application to vision based robotics. Generally, object (foreground) and background have certain discriminative geometric information in 3D space. By exploring the 3D information from multiple views, our proposed method can segment potential objects correctly and automatically compared to conventional unsupervised segmentation using only 2D visual cues. Experiments with real video data collected from indoor and outdoor environments verify the proposed approach.

Vision-based place recognition : how low can you go?

In this paper we use the algorithm SeqSLAM to address the question, how little and what quality of visual information is needed to localize along a familiar route? We conduct a comprehensive investigation of place recognition performance on seven datasets while varying image resolution (primarily 1 to 512 pixel images), pixel bit depth, field of view, motion blur, image compression and matching sequence length. Results confirm that place recognition using single images or short image sequences is poor, but improves to match or exceed current benchmarks as the matching sequence length increases. We then present place recognition results from two experiments where low-quality imagery is directly caused by sensor limitations; in one, place recognition is achieved along an unlit mountain road by using noisy, long-exposure blurred images, and in the other, two single pixel light sensors are used to localize in an indoor environment. We also show failure modes caused by pose variance and sequence aliasing, and discuss ways in which they may be overcome. By showing how place recognition along a route is feasible even with severely degraded image sequences, we hope to provoke a re-examination of how we develop and test future localization and mapping systems.

Analysis of the design-construction supply chain in the thermal performance of sub-tropical and tropical housing

Background: In sub-tropical and tropical Queensland, a legacy of poor housing design,minimal building regulations with few compliance measures, an absence of post-construction performance evaluation and various social and market factors has led to a high and growing penetration of, and reliance on, air conditioners to provide thermal comfort for occupants. The pervasive reliance on air conditioners has arguably impacted on building forms, changed cultural expectations of comfort and social practices for achieving comfort, and may have resulted in a loss of skills in designing and constructing high performance building envelopes. Aim: The aim of this paper is to report on initial outcomes of a project that sought to determine how the predicted building thermal performance of twenty-five houses in subtropical and tropical Queensland compared with objective performance measures and comfort performance as perceived by occupants. The purpose of the project was to shed light on the role of various supply chain agents in the realisation of thermal performance outcomes. Methodology: The case study methodology embraced a socio-technical approach incorporating building science and sociology. Building simulation was used to model thermal performance under controlled comfort assumptions and adaptive comfort conditions. Actual indoor climate conditions were measured by temperature and relative humidity sensors placed throughout each house, whilst occupants’ expectations of thermal comfort and their self-reported behaviours were gathered through semi-structured interviews and periodic comfort surveys. Thermal imaging and air infiltration tests, along with building design documents, were analysed to evaluate the influence of various supply chain agents on the actual performance outcomes. Results: The results clearly show that in the housing supply chain – from designer to constructor to occupant – there is limited understanding from each agent of their role in contributing to, or inhibiting, occupants’ comfort.

Spatial variation of air pollutants in a multilevel office building

Within-building spatial variability of indoor air quality may influence substantially the reliability of human exposure assessments based on single point samples, but have hitherto been little studied. To investigate and understand the within-building spatial variation of air pollutants, field measurements were conducted in a 7 level office building in Brisbane, Australia. The building consists of 3 sections (A side, Meddler and B side).

Personal exposure to ultrafine particles : the influence of time-activity patterns

Exposure to ultrafine particles (UFPs) is deemed to be a major risk affecting human health. Therefore, airborne particle studies were performed in the recent years to evaluate the most critical micro-environments, as well as identifying the main UFP sources. Nonetheless, in order to properly evaluate the UFP exposure, personal monitoring is required as the only way to relate particle exposure levels to the activities performed and micro-environments visited. To this purpose, in the present work, the results of experimental analysis aimed at showing the effect of the time-activity patterns on UFP personal exposure are reported. In particular, 24 non-smoking couples (12 during winter and summer time, respectively), comprised of a man who worked full-time and a woman who was a homemaker, were analyzed using personal particle counter and GPS monitors. Each couple was investigated for a 48-h period, during which they also filled out a diary reporting the daily activities performed. Time activity patterns, particle number concentration exposure and the related dose received by the participants, in terms of particle alveolar-deposited surface area, were measured. The average exposure to particle number concentration was higher for women during both summer and winter (Summer: women 1.8×104 part. cm-3; men 9.2×103 part. cm-3; Winter: women 2.9×104 part. cm-3; men 1.3×104 part. cm-3), which was likely due to the time spent undertaking cooking activities. Staying indoors after cooking also led to higher alveolar-deposited surface area dose for both women and men during the winter time (9.12×102 and 6.33×102 mm2, respectively), when indoor ventilation was greatly reduced. The effect of cooking activities was also detected in terms of women’s dose intensity (dose per unit time), being 8.6 and 6.6 in winter and summer, respectively. On the contrary, the highest dose intensity activity for men was time spent using transportation (2.8 in both winter and summer).

Measurement, modelling and capacity analysis for novel, fixed multi-user single-antenna MIMO-OFDM system, in rural environments

High-speed broadband internet access is widely recognised as a catalyst to social and economic development. However, the provision of broadband Internet services with the existing solutions to rural population, scattered over an extensive geographical area, remains both an economic and technical challenge. As a feasible solution, the Commonwealth Scientific and Industrial Research Organization (CSIRO) proposed a highly spectrally efficient, innovative and cost-effective fixed wireless broadband access technology, which uses analogue TV frequency spectrum and Multi-User MIMO (MUMIMO) technology with Orthogonal-Frequency-Division-Multiplexing (OFDM). MIMO systems have emerged as a promising solution for the increasing demand of higher data rates, better quality of service, and higher network capacity. However, the performance of MIMO systems can be significantly affected by different types of propagation environments e.g., indoor, outdoor urban, or outdoor rural and operating frequencies. For instance, large spectral efficiencies associated with MIMO systems, which assume a rich scattering environment in urban environments, may not be valid for all propagation environments, such as outdoor rural environments, due to the presence of less scatterer densities. Since this is the first time a MU-MIMO-OFDM fixed broadband wireless access solution is deployed in a rural environment, questions from both theoretical and practical standpoints arise; For example, what capacity gains are available for the proposed solution under realistic rural propagation conditions?. Currently, no comprehensive channel measurement and capacity analysis results are available for MU-MIMO-OFDM fixed broadband wireless access systems which employ large scale multiple antennas at the Access Point (AP) and analogue TV frequency spectrum in rural environments. Moreover, according to the literature, no deterministic MU-MIMO channel models exist that define rural wireless channels by accounting for terrain effects. This thesis fills the aforementioned knowledge gaps with channel measurements, channel modeling and comprehensive capacity analysis for MU-MIMO-OFDM fixed wireless broadband access systems in rural environments. For the first time, channel measurements were conducted in a rural farmland near Smithton, Tasmania using CSIRO's broadband wireless access solution. A novel deterministic MU-MIMO-OFDM channel model, which can be used for accurate performance prediction of rural MUMIMO channels with dominant Line-of-Sight (LoS) paths, was developed under this research. Results show that the proposed solution can achieve 43.7 bits/s/Hz at a Signal-to- Noise Ratio (SNR) of 20 dB in rural environments. Based on channel measurement results, this thesis verifies that the deterministic channel model accurately predicts channel capacity in rural environments with a Root Mean Square (RMS) error of 0.18 bits/s/Hz. Moreover, this study presents a comprehensive capacity analysis of rural MU-MIMOOFDM channels using experimental, simulated and theoretical models. Based on the validated deterministic model, further investigations on channel capacity and the eects of capacity variation, with different user distribution angles (θ) around the AP, were analysed. For instance, when SNR = 20dB, the capacity increases from 15.5 bits/s/Hz to 43.7 bits/s/Hz as θ increases from 10° to 360°. Strategies to mitigate these capacity degradation effects are also presented by employing a suitable user grouping method. Outcomes of this thesis have already been used by CSIRO scientists to determine optimum user distribution angles around the AP, and are of great significance for researchers and MU-MUMO-OFDM system developers to understand the advantages and potential capacity gains of MU-MIMO systems in rural environments. Also, results of this study are useful to further improve the performance of MU-MIMO-OFDM systems in rural environments. Ultimately, this knowledge contribution will be useful in delivering efficient, cost-effective high-speed wireless broadband systems that are tailor-made for rural environments, thus, improving the quality of life and economic prosperity of rural populations.

Reflections on chemistry sessions at the 2012 Healthy Buildings Conference

Scores of well-researched individual papers and posters specifically or indirectly addressing the occurrence, measurement or exposure impacts of chemicals in buildings were presented at 2012 Healthy Buildings Conference. Many of these presentations offered advances in sampling and characterisation of chemical pollutants while others extended the frontiers of knowledge on the emission, adsorption, risk, fate and compositional levels of chemicals in indoor and outdoor microenvironments. Several modelled or monitored indoor chemistry, including processes that generated secondary pollutants. This article provides an overview of the state of knowledge on healthy buildings based on papers presented in chemistry sessions at Healthy Buildings 2012 (HB2012) Conference. It also suggests future directions in healthy buildings research.

School children’s personal exposure to ultrafine particles in the urban environment

There has been considerable scientific interest in personal exposure to ultrafine particles (UFP). In this study, the inhaled particle surface area doses and dose relative intensities in the tracheobronchial and alveolar regions of lungs were calculated using the measured 24-hour UFP time series of school children personal exposures for each recorded activity. Bayesian hierarchical modelling was used to determine mean doses and dose intensities for the various microenvironments. Analysis of measured personal exposures for 137 participating children from 25 schools in the Brisbane Metropolitan Area showed similar trends for all the participating children. Bayesian regression modelling was performed to calculate the daily proportion of children's total doses at different microenvironments. The proportion of alveolar doses in the total daily dose for \emph{home}, \emph{school}, \emph{commuting} and \emph{other} were 55.3\%, 35.3\%, 4.5\% and 5.0\%, respectively, with the \emph{home} microenvironment contributing a majority of children's total daily dose. Children's mean indoor dose was never higher than the outdoor's at any of the schools, indicating there were no persistent indoor particle sources in the classrooms during the measurements. Outdoor activities, eating/cooking at home and commuting were the three activities with the highest dose intensities. Personal exposure was more influenced by the ambient particle levels than immediate traffic.

Odometry-driven inference to link multiple exemplars of a location

A major challenge for robot localization and mapping systems is maintaining reliable operation in a changing environment. Vision-based systems in particular are susceptible to changes in illumination and weather, and the same location at another time of day may appear radically different to a system using a feature-based visual localization system. One approach for mapping changing environments is to create and maintain maps that contain multiple representations of each physical location in a topological framework or manifold. However, this requires the system to be able to correctly link two or more appearance representations to the same spatial location, even though the representations may appear quite dissimilar. This paper proposes a method of linking visual representations from the same location without requiring a visual match, thereby allowing vision-based localization systems to create multiple appearance representations of physical locations. The most likely position on the robot path is determined using particle filter methods based on dead reckoning data and recent visual loop closures. In order to avoid erroneous loop closures, the odometry-based inferences are only accepted when the inferred path's end point is confirmed as correct by the visual matching system. Algorithm performance is demonstrated using an indoor robot dataset and a large outdoor camera dataset.

Brain-inspired sensor fusion for navigating robots

Current state of the art robot mapping and navigation systems produce impressive performance under a narrow range of robot platform, sensor and environmental conditions, in contrast to animals such as rats that produce “good enough” maps that enable them to function under an incredible range of situations. In this paper we present a rat-inspired featureless sensor-fusion system that assesses the usefulness of multiple sensor modalities based on their utility and coherence for place recognition, without knowledge as to the type of sensor. We demonstrate the system on a Pioneer robot in indoor and outdoor environments with abrupt lighting changes. Through dynamic weighting of the sensors, the system is able to perform correct place recognition and mapping where the static sensor weighting approach fails.